As early as the 1950’s, Rose advocated for the idea that individuals should be treated based on bell curves of an entire population, essentially risk based medicine. This philosophy would lie at the heart of not only the British National Health Service but many public health programs. It informed the famous Framingham studies here in the U.S. In fact, the term “population medicine” is a very positive term for those working in healthcare today. Genomic medicine has been an outgrowth of population medicine.

Michel says this philosophy is failing us at the level of individual health. Third party payers, be they governments or insurance companies, are in their offices working a system based on large datasets. They develop algorithms using all kinds of risk studies. But these payers have little to no contact with the actual patients. Ironically, he says, we call it personalized medicine. Michel points to hypertension, a disease area where sixty years after Rose pushed for risk studies, cardiologists are still divided into camps over whether to treat a patient if their blood pressure lies above the average. Michel argues that population medicine is utilitarian and ultimately utopian. What are framed as scientific studies are really social engineering.

What about clinical trials, we ask Michel. Don't population studies bring doctors and patients many good drugs?

In the second half of the interview, Michel points out that a mechanistic view of biology dominates clinicians and scientists today. It’s true. Our guest last week, a well known geneticist from Stanford, compared people to cars, arguing for the need to wear health data gathering sensors.

"Right now among philosophers of science, there’s a recognition that “mechanism” is inadequate to explain cellular organisms." The study of biology also has often been developed with tautologies, he says. "For example, say you’re studying the beaver and you ask what is a beaver. The standard answer is to go to the genetic sequence. From the genetics, you say you have a beaver. But you have to know what beavers are in the first place in order to study a beaver. It’s a circular argument."

So what other models might we use in biology? And what can we do in healthcare if we’re not using large population studies--go back to blood letting?